feat: add Vlasov 2D distributed initialization#285
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…rd_to_partitioned - helpers.py: compute each component's density profile once and reuse for both n_prof_species and the unsharded f_one path (previously evaluated twice on the host path). - distributed.py: docstring note on reshard_for_global_axis_fft warning that declaring shardings on jax.jit lets XLA's SPMD partitioner do this work automatically. Add symmetric reshard_to_partitioned helper that restores the canonical partitioned layout (typically used after an inverse FFT). - tests: round-trip test for reshard_for_global_axis_fft + reshard_to_partitioned. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Summary
grid.distribution-shardingconfig for Vlasov-2D distribution initializationNamedShardinghelpers andmake_array_from_callbackmachinery to initialize globalf(x, y, vx, vy)arrays shard-by-shardNotes
grid.distribution-sharding.enabledis truenoise_type: noneornoise_val: 0.0) because the existing noise profile is shape-seeded and would otherwise repeat per shardreshard_for_global_axis_ffthelperVerification
uvx ruff format adept/_vlasov2d tests/test_vlasov2d/test_distributed_init.pyuvx ruff check adept/_vlasov2d tests/test_vlasov2d/test_distributed_init.pyuv run pytest tests/test_vlasov2d/test_distributed_init.py -q→ 4 passeduv run pytest tests/test_vlasov2d -q; existing long solver case was still CPU-bound after ~20 minutes, so I stopped it after the targeted tests had passed